2015-03-31T18:22:10ZDon’t break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrainhttp://hdl.handle.net/1957/55429
Don’t break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrain
Birn-Jeffery, Aleksandra V.; Hubicki, Christian M.; Blum, Yvonne; Renjewski, Daniel; Hurst, Jonathan W.; Daley, Monica A.
Cursorial ground birds are paragons of bipedal running that span a
500-fold mass range from quail to ostrich. Here we investigate the
task-level control priorities of cursorial birds by analysing how they
negotiate single-step obstacles that create a conflict between body
stability (attenuating deviations in body motion) and consistent leg
force–length dynamics (for economy and leg safety). We also test the
hypothesis that control priorities shift between body stability and leg
safety with increasing body size, reflecting use of active control to
overcome size-related challenges. Weight-support demands lead to
a shift towards straighter legs and stiffer steady gait with increasing
body size, but it remains unknown whether non-steady locomotor
priorities diverge with size. We found that all measured species used
a consistent obstacle negotiation strategy, involving unsteady body
dynamics to minimise fluctuations in leg posture and loading across
multiple steps, not directly prioritising body stability. Peak leg forces
remained remarkably consistent across obstacle terrain, within 0.35
body weights of level running for obstacle heights from 0.1 to 0.5
times leg length. All species used similar stance leg actuation
patterns, involving asymmetric force–length trajectories and posture-dependent
actuation to add or remove energy depending on landing
conditions. We present a simple stance leg model that explains key
features of avian bipedal locomotion, and suggests economy as a
key priority on both level and uneven terrain. We suggest that running
ground birds target the closely coupled priorities of economy and leg
safety as the direct imperatives of control, with adequate stability
achieved through appropriately tuned intrinsic dynamics.
This is the publisher’s final pdf. The published article is copyrighted by the Company of Biologists Ltd and can be found at: http://jeb.biologists.org/.
2014-11-01T00:00:00ZMultirobot Coordination for Space Explorationhttp://hdl.handle.net/1957/55277
Multirobot Coordination for Space Exploration
Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan
Teams of artificially intelligent planetary rovers have tremendous potential for space exploration, allowing for reduced cost, increased flexibility, and increased reliability. However, having these multiple autonomous devices acting simultaneously leads to a problem of coordination: to achieve the best results, they should work together. This is not a simple task. Due to the large distances and harsh environments, a rover must be able to perform a wide variety of tasks with a wide variety of potential teammates in uncertain and unsafe environments. Directly coding all the necessary rules that can reliably handle all of this coordination and uncertainty is problematic. Instead, this article examines tackling this problem through the use of coordinated reinforcement learning: rather than being programmed what to do, the rovers iteratively learn through trial and error to take take actions that lead to high overall system return. To allow for coordination, yet allow each agent to learn and act independently, we employ state-of-the-art reward-shaping techniques. This article uses visualization techniques to break down complex performance indicators into an accessible form and identifies key future research directions.
To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by the American Association for Artificial Intelligence and can be found at: http://www.aaai.org/Magazine/magazine.php.
2014-01-01T00:00:00ZMechanism reduction for multicomponent surrogates: A case study using toluene reference fuelshttp://hdl.handle.net/1957/55250
Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels
Niemeyer, Kyle E.; Sung, Chih-Jen
Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, such as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.
This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/combustion-and-flame/
2014-11-01T00:00:00ZSampling-based robotic information gathering algorithmshttp://hdl.handle.net/1957/55134
Sampling-based robotic information gathering algorithms
Hollinger, Geoffrey A.; Sukhatme, Gaurav S.
We propose three sampling-based motion planning algorithms for generating informative mobile robot trajectories. The goal is to find a trajectory that maximizes an information quality metric (e.g. variance reduction, information gain, or mutual information) and also falls within a pre-specified budget constraint (e.g. fuel, energy, or time). Prior algorithms have employed combinatorial optimization techniques to solve these problems, but existing techniques are typically restricted to discrete domains and often scale poorly in the size of the problem. Our proposed rapidly exploring information gathering (RIG) algorithms combine ideas from sampling-based motion planning with branch and bound techniques to achieve efficient information gathering in continuous space with motion constraints. We provide analysis of the asymptotic optimality of our algorithms, and we present several conservative pruning strategies for modular, submodular, and time-varying information objectives. We demonstrate that our proposed techniques find optimal solutions more quickly than existing combinatorial solvers, and we provide a proof-of-concept field implementation on an autonomous surface vehicle performing a wireless signal strength monitoring task in a lake.
This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the Author(s) and published by SAGE Publications. It can be found at: http://ijr.sagepub.com/
2014-08-01T00:00:00Z